Author

Jia-Qi Lu

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Preprint Aug 2026

Sharp Characterization of Bias in Post-Bandit Inference

This work identifies the algorithmic origin of bias through a key index-function-dependent quantity, which is term effective exploration rate, and shows how bias most severely distorts confidence intervals and hypothesis tests when the tested arm is one of the tied-optimal arms.

Li-Su Wang, Yi-Lun Chen, Jia-Qi Lu · 0 citations

#data science Preprint Aug 2026

Characterizing Bias in Post-Bandit Inference under Index Algorithms

Bandit algorithms generate data for downstream inference, but adaptive sampling biases post-bandit sample means. We analyze this bias for stable index algorithms, including UCB1 and its generalizations, and derive sharp leading-order expressions for the sample-mean bias and expected $Z$-statistic. Our characterization...

Lisu Wang, Yilun Chen, Jiaqi Lu · 0 citations